Hui Lu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Hui Lu has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
Da Fang
Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
2 shared publications- Xianghua Ma
Jiangsu Province People’s Hospital, The First Affiliated Hospital with Nanjing Medical University
2 shared publications Ying Liu
Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
2 shared publicationsBihui Pan
Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China
1 shared publicationLi Xu
Department of Nutriology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China
1 shared publicationLu Xu
Department of Nutriology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China (mainland)
1 shared publication
Latest Publications
- 10 December 2019
- Published by International Scientific Information, Inc. in Medical Science Monitor
- Vol. 25, 9409-9415
A Predictive Model to Distinguish Papillary Thyroid Carcinomas from Benign Thyroid Nodules Using Ultrasonographic Features: A Single-Center, Retrospective Analysis
BACKGROUND:We developed a model based on ultrasound (US) features of thyroid nodules and cervical lymph nodes to distinguish papillary thyroid carcinomas (PTC) from benign thyroid nodules. MATERIAL AND METHODS:We retrospectively collected data on pre...
- 10 December 2019
- Published by International Scientific Information, Inc. in Medical Science Monitor
- Vol. 25, 9409-9415
A Predictive Model to Distinguish Papillary Thyroid Carcinomas from Benign Thyroid Nodules Using Ultrasonographic Features: A Single-Center, Retrospective Analysis
BACKGROUND:We developed a model based on ultrasound (US) features of thyroid nodules and cervical lymph nodes to distinguish papillary thyroid carcinomas (PTC) from benign thyroid nodules. MATERIAL AND METHODS:We retrospectively collected data on pre...
- Open Access
- 20 August 2019
- Published by Hindawi Limited in BioMed Research International
- Vol. 2019, 1-11
The Diagnostic Performance of Afirma Gene Expression Classifier for the Indeterminate Thyroid Nodules: A Meta-Analysis
Background. Approximately 15 to 30% of thyroid nodules evaluated by fine-needle aspiration (FNA) were classified as indeterminate; the accurate diagnostic molecular tests of these nodules remain a challenge. We aimed to evaluate the diagnostic performance of Afirma gene expression classifier (GEC) for the indeterminate thyroid nodules (ITNs). Methods. Studies published from January 2005 to December 2018 were systematically reviewed. The gold reference standard relied on the histopathologic results diagnosis from thyroidectomy surgical specimens. MetaDisc software was used to investigate the pooled sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curves. Results. A total of 18 studies involving 5290 patients with 3290 cases of ITNs were included. Collected data revealed that the pooled sensitivity of GEC was 95.5% (95% CI 93.3%–97.0%, p < 0.001), the specificity was 22.1% (95% CI 19.4%-24.9%, p < 0.001), the NPV was 88.2% (95% CI 0.833–0.921, p < 0.001), the PPV was 44.3% (95% CI 0.416–0.471, p < 0.001), and the DOR was 5.25 (95% CI 3.42–8.04, p= 0.855). Conclusion. The GEC has quite high sensitivity of 95.5% but low specificity of 22.1%. The high sensitivity makes it probable to rule out malignant nodules. Thus, over half of nodules with GEC-suspicious results still require further validation like molecular markers, diagnostic surgery, or long follow-up, which limits its use in future clinical practice.
- 20 August 2019
- Published by Hindawi Limited in BioMed Research International
- Vol. 2019, 1-11
Open AccessThe Diagnostic Performance of Afirma Gene Expression Classifier for the Indeterminate Thyroid Nodules: A Meta-Analysis
Background. Approximately 15 to 30% of thyroid nodules evaluated by fine-needle aspiration (FNA) were classified as indeterminate; the accurate diagnostic molecular tests of these nodules remain a challenge. We aimed to evaluate the diagnostic performance of Afirma gene expression classifier (GEC) for the indeterminate thyroid nodules (ITNs). Methods. Studies published from January 2005 to December 2018 were systematically reviewed. The gold reference standard relied on the histopathologic results diagnosis from thyroidectomy surgical specimens. MetaDisc software was used to investigate the pooled sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curves. Results. A total of 18 studies involving 5290 patients with 3290 cases of ITNs were included. Collected data revealed that the pooled sensitivity of GEC was 95.5% (95% CI 93.3%–97.0%, p < 0.001), the specificity was 22.1% (95% CI 19.4%-24.9%, p < 0.001), the NPV was 88.2% (95% CI 0.833–0.921, p < 0.001), the PPV was 44.3% (95% CI 0.416–0.471, p < 0.001), and the DOR was 5.25 (95% CI 3.42–8.04, p= 0.855). Conclusion. The GEC has quite high sensitivity of 95.5% but low specificity of 22.1%. The high sensitivity makes it probable to rule out malignant nodules. Thus, over half of nodules with GEC-suspicious results still require further validation like molecular markers, diagnostic surgery, or long follow-up, which limits its use in future clinical practice.